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AIRCRAFT MAINTENANCE PREDICTIVE ANALYSIS (Data Mining) 25 Jan 07 OKLAHOMA CITY AIR LOGISTICS CENTER TEAM TINKER Mr. Bob Wright OC-ALC/ENFO Robert.email@example.com I n t e g r i t y - S e r v i c e - E x c e l l e n c e Problem
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AIR LOGISTICS CENTER
Mr. Bob Wright
I n t e g r i t y - S e r v i c e - E x c e l l e n c e
Many USAF airframe’s average age are at or beyond design limits and experiencing growing unpredicted component failures
Current damage analyses for structural components do not consider extensive maintenance activity accomplished on these airframes
Much relevant maintenance data (description of defects found, or repair accomplished) is either captured on paper only, or not captured at all; and not related to a specific a/c
MIL-STD-1530C (Aircraft Structural Integrity Program)
184.108.40.206 Structural maintenance database development.
The structural maintenance database shall be developed to capture adequate, detailed information on the aging processes (fatigue, corrosion, delaminations, etc.) which occur in the aircraft and thus support the ongoing evaluation of structural integrity during sustainment. The database shall be developed to record all significant damage findings such as cracks, corrosion, and/or delaminations discovered during program depot maintenance, analytical condition inspections, time compliance technical order (TCTO) structural inspections, teardown inspections, and normal operational maintenance. The database shall also be able to record a description of the damage types, damage sizes, damage locations, inspection techniques (including POD information), aircraft configuration, pertinent aircraft usage history including basing information, and corrosion preventive methods (e.g., wash cycles, coatings, etc.). The database shall also be able to record all significant repairs and/or modifications so as to maintain configuration control. These records shall include a description of the repair/modification and when it was incorporated. Additional considerations for data to be recorded shall facilitate the analysis update described in 5.5.6.
Provide quantitative information for decisions related to individual aircraft and fleet system health.
Acquire, consolidate, and evaluate maintenance data to provide a continual update of the health of operational aircraft.
Significant damage findings during PDM
Analytical Condition Inspections/results
TCTO structural Inspections/results
Field -3 repairs
Identify/use existing Air Force systems when possible
Depot and Field level (i.e. CAMS, PDMSS, G081, etc.)
Provide alternative solutions for data short falls.
Damage size, type, and location.
Modification and repair actions.
327th ASW ASIP managers need trending analysis relating actual defects found to aircraft usage
76 MXW needs to anticipate incoming non predicted defects based on aircraft usage and PDM history ASIMIS / G050
ASC and Fleet Viability Board need to view current fleet status and future repair requirements to determine best course of action for airframes
New Mil-Std 1530C Task V (sustainment) goal
Actual Fleet Condition
Automated Process Guide – Automates inspection processes utilizing mobile data collection devices
Ensures standardization and complete inspections
More accurate tie to WUC and HMC technical data codes
Labor Analysis – Provides visibility into work flow including back shops and support processes
Flags labor problem areas for individual analysis
Low Percent Analysis – Anticipates incoming non predicted defects based on aircraft usage and PDM history (not a reliability study!!)
Quality Data Analysis – Analyzes aircraft defects to provide root cause and trend analysis
ASIMIS collects usage history per tail number
Flight hours, landings, fuel offloads, time @ mach/alt
76 MXW will collect defect/repair information per tail number
We still need tools to query defect information captured during maintenance and display against usage data to enable trending analysis
Randel Bowman, 76 AMXG/QIQ
Bob Wright, OC-ALC/ENFO
Ken Simmons, OC-ALC/ENET